National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Finance Data Analyst

Hutcheon Mearns
Blairgowrie
2 days ago
Create job alert

Hutcheon Mearns are delighted to be recruiting on behalf of our established client; a fast-scaling, forward-thinking organisation for a Finance Data Analyst to join their team for a 3 to 6 month period to aid them through a busy period. There is an opportunity that this position could go permanent for the right individual. This job offers a salary of £30,000 - £40,000 depending on experience and is full time in the office based near Coupar Angus. Once trained, there may be an opportunity for hybrid working.



The Opportunity



Working within the finance operations team, you will actively support the business by providing an effective and professional knowledge covering large data set reporting and analysis, management reporting, mathematical and statistical modelling and coding.



Your responsibilities will include:




  • Transform and model raw financial and operational data into structured, insightful outputs for analysis and reporting
  • Cleanse and validate datasets to ensure accuracy, consistency, and reliability
  • Identify trends, patterns, and anomalies within financial data to provide actionable insights
  • Deliver clear, insightful analysis and reporting through dashboards, presentations, and written reports tailored to business needs
  • Collaborate across departments to understand reporting requirements and ensure the delivery of timely, relevant data
  • Produce and maintain regular (daily, weekly, monthly) KPI reports to inform both financial and non-financial decision-making
  • Support internal and external audit processes through data extraction, reconciliation, and documentation
  • Assist in the continuous improvement of data processes, including identifying inefficiencies and recommending solutions
  • Work cross-functionally to respond to data-related queries, providing support and training where necessary


The Candidate



You will ideally be educated to Degree level within a relevant subject (Finance, Maths, Statistics, Data Science etc). You will have previous experience working within a data environment. You will possess advanced Excel skills and ideally have experience with Power BI. You will be highly numerate with strong analytical skills. You will be able to work in a fast paced environment accurately and be confident in looking for errors within data. You will be immediately available or available on short notice (1 week).



Benefits and conditions 




  • Temporary position for 3 to 6 months with the potential to go permanent
  • Salary of £30,000 - £40,000 depending on experience
  • Potential for hybrid working once fully trained


Next steps?



If you consider yourself to be a commercially minded Data Analyst, this could be a great role for you!  Apply with your full CV to the position asap!  


Related Jobs

View all jobs

Finance Data Analyst

Finance Data Analyst

Finance Data Analyst

Commercial Finance Data Analyst

Temporary Finance Data Analyst | £30,000 - £40,000 | Coupar Angus

Data Analyst – Business Analytics (12 month FTC)

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.